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Statistics and Data Science Seminar Vladimir Koltchinskii (Georgia Institute of Technology)

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Statistics and Data Science Seminar Guy Bresler (MIT)

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Statistics and Data Science Seminar Lutz Warnke (Georgia Institute of Technology)

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Bias Reduction and Asymptotic Efficiency in Estimation of Smooth Functionals of High-Dimensional Covariance

Vladimir Koltchinskii (Georgia Institute of Technology)
E18-304

Abstract: We discuss a recent approach to bias reduction in a problem of estimation of smooth functionals of high-dimensional parameters of statistical models. In particular, this approach has been developed in the case of estimation of functionals of covariance operator Σ : Rd d → Rd of the form f(Σ), B based on n i.i.d.…

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Reducibility and Computational Lower Bounds for Some High-dimensional Statistics Problems

Guy Bresler (MIT)
E18-304

Abstract: The prototypical high-dimensional statistics problem entails finding a structured signal in noise. Many of these problems exhibit an intriguing phenomenon: the amount of data needed by all known computationally efficient algorithms far exceeds what is needed for inefficient algorithms that search over all possible structures. A line of work initiated by Berthet and Rigollet…

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Large girth approximate Steiner triple systems

Lutz Warnke (Georgia Institute of Technology)
E18-304

Abstract: In 1973 Erdos asked whether there are n-vertex partial Steiner triple systems with arbitrary high girth and quadratically many triples. (Here girth is defined as the smallest integer g \ge 4 for which some g-element vertex-set contains at least g-2 triples.) We answer this question, by showing existence of approximate Steiner triple systems with…

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